no code implementations • 10 Nov 2023 • Yinsong Xu, Jiaqi Tang, Aidong Men, Qingchao Chen
Then, we incorporate the human prior into the prompts, which is vital for alleviating the domain gap between natural and medical images and enhancing the applicability and usefulness of SAM in medical scenarios.
no code implementations • 6 Aug 2023 • Yinsong Xu, Aidong Men, Yang Liu, Qingchao Chen
To answer the first question, we empirically observed an interesting Spontaneous Pulling (SP) Effect in fine-tuning where the discrepancies between any two of the three domains (ImageNet, Source, Target) decrease but at the cost of the impaired semantic structure of the pre-train domain.
1 code implementation • 28 Aug 2022 • Yinsong Xu, Zhuqing Jiang, Aidong Men, Yang Liu, Qingchao Chen
Existing domain adaptation methods assume that domain discrepancies are caused by a few discrete attributes and variations, e. g., art, real, painting, quickdraw, etc.